"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"Из графика видно, что все каналы показывают схожую между собой динамику установок как в дни наибольшей активности, так и в другие периоды, а пиковые дни инсталлов совпадают с пиками активности пользователей в приложении."
],
"metadata": {
"id": "wi4jnQxVhnjh"
}
},
{
"cell_type": "markdown",
"source": [
"Посмотрим на итоговую результативность каналов привлечения по количеству установок приложения в рассматриваемом периоде. Для этого создадим сводную таблицу *installs_df,* в которой подсчитаем количество установок в разрезе источников привлечения. Отсортируем её по убыванию количества установок и добавим столбец с долей каждого источника привлечения. Для визуализации полученных результатов используем столбчатую диаграмму из модуля plotly.graph_objects библиотеки plotly. По оси абсцисс расположим каналы привлечения, по оси ординат - количество установок приложения."
],
"metadata": {
"id": "KPMjFtaFT12M"
}
},
{
"cell_type": "code",
"source": [
"installs_df = pd.pivot_table(df[df['event'] == 'app_install'], values=['device_id'], index=['utm_source'], aggfunc='nunique').reset_index()\n",
"installs_df.rename({'device_id': 'installs_count'}, axis=1, inplace=True)\n",
"installs_df = installs_df.sort_values('installs_count', ignore_index=True, ascending=False)\n",
"installs_df['installs_ratio'] = round(installs_df['installs_count'] * 100 / installs_df['installs_count'].sum(), 1)\n",
"display(installs_df)\n",
"print()\n",
"print('Ответ на первый вопрос Задания 1.1.4: С канала \"{}\" было больше всего инсталлов.'.format(installs_df['utm_source'][1]))"
],
"metadata": {
"id": "LUUQ4_vpX5C6",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 304
},
"outputId": "cf8709e0-55a2-4fca-e677-ca9edb1c128f"
},
"execution_count": 117,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" utm_source installs_count installs_ratio\n",
"0 not_defined 32460 21.0\n",
"1 yandex-direct 29368 19.0\n",
"2 google_ads 26286 17.0\n",
"3 vk_ads 23189 15.0\n",
"4 instagram_ads 20096 13.0\n",
"5 facebook_ads 13916 9.0\n",
"6 referal 9282 6.0"
],
"text/html": [
"\n",
"
"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"Отметим, что все каналы показывают схожую между собой динамику привлечения новых пользователей, а пиковые дни привлечения совпадают с днями наибольшей активности в приложении. \n",
"\n",
"**Выводы.**\n",
"\n",
"Проведённый анализ динамики установок приложения и привлечения пользователей указывает на то, что периоды пиковой активности в приложении, на которые мы обратили внимание ранее, были сформированы в основном за счёт активного привлечения новых пользователей. Возможно это были дни запуска новых рекламных кампаний и закупки трафика/инсталлов.\n",
"\n",
"**Предложения.**\n",
"\n",
"Для более плавной генерации активности пользователями нашего сервиса можно разделить во времени запуск рекламных кампаний в разных каналах привлечения, а после настройки ежедневного мониторинга активности пользователей в случаях её падения запускать акции и скидки.\n",
"Для роста активности действующих пользователей в рабочие дни можно использовать рассылки пуш-уведомлений с призывом к действию, который должен возвращать пользователей в приложение. Уведомления могут содержать товарные рекомендации, которые могут быть настроены как на интересы конкретного пользователя (товары, которые он ранее просматривал, добавлял в корзину или покупал), так и на популярные товары, а также напоминать об оставленных в корзине товарах."
],
"metadata": {
"id": "n85S1MhOjMQP"
}
},
{
"cell_type": "markdown",
"source": [
"Посмотрим на итоговую результативность рекламных каналов по привлечению новых пользователей. Для этого создадим сводную таблицу *first_start_df,* в которой подсчитаем количество первых открытий приложения за рассматриваемый период в разрезе источников привлечения. Чтобы учесть только первые открытия для каждого *device_id,* отсортируем данные исходной таблицы по дате открытия приложения по возрастанию и удалим строки с вторыми и последующими совпадающими *device_id.* Отсортируем полученную таблицу по убыванию количества открытий и добавим столбец с долей каждого источника привлечения. Для визуализации полученных результатов используем столбчатую диаграмму. По оси абсцисс расположим каналы привлечения, по оси ординат - количество первых открытий приложения."
],
"metadata": {
"id": "4eqRI7UjlfpO"
}
},
{
"cell_type": "code",
"source": [
"first_start_df = pd.pivot_table(df[df['event'] == 'app_start'].sort_values('date').drop_duplicates('device_id'), values=['event'], index=['utm_source'], aggfunc=len).reset_index()\n",
"first_start_df.rename({'event': 'app_start_count'}, axis=1, inplace=True)\n",
"first_start_df = first_start_df.sort_values('app_start_count', ignore_index=True, ascending=False)\n",
"first_start_df['app_start_ratio'] = round(first_start_df['app_start_count'] * 100 / first_start_df['app_start_count'].sum(), 1)\n",
"display(first_start_df)\n",
"print()\n",
"print('Ответ на второй вопрос Задания 1.1.4: С канала \"{}\" было больше всего первых открытий приложения.'.format(first_start_df['utm_source'][1]))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 304
},
"id": "m--AJ7z-jqPB",
"outputId": "209dc1e3-20b7-4a8f-9da2-1aba1738bc00"
},
"execution_count": 121,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" utm_source app_start_count app_start_ratio\n",
"0 not_defined 41456 21.7\n",
"1 yandex-direct 34441 18.0\n",
"2 google_ads 31437 16.5\n",
"3 vk_ads 27905 14.6\n",
"4 instagram_ads 24818 13.0\n",
"5 facebook_ads 18844 9.9\n",
"6 referal 11983 6.3"
],
"text/html": [
"\n",
"
"
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"***Самыми результативными из платных каналов по привлечению новых пользователей в приложение оказались те же Яндекс, Гугл и ВК (их доли в общем объёме привлечения 18%, 17% и 15% соответственно), а в аутсайдерах по прежнему находится реферальная программа (с долей в 6%).***"
],
"metadata": {
"id": "5gKnqKEfrt6f"
}
},
{
"cell_type": "markdown",
"source": [
"Посмотрим, как в рассматриваемом периоде распределён трафик в приложении.\n",
"Для начала добавим в исходную таблицу столбец с датой установки приложения пользователями и определим для каждого события, какие из них были совершены в день установки приложения, а какие позднее.\n",
"\n",
"Создадим словарь *install_dates_dict*, содержащий *device_id* и соответствующие даты установки и с помощью lambda-функции пройдёмся по значениям столбца *device_id* для заполнения из полученного словаря дат установки приложения в столбец *install_date*. Создадим новый столбец *install_same_day,* который заполним значениями True для тех событий, которые произошли в день установки приложения, и False для тех, которые произошли в другую дату."
],
"metadata": {
"id": "bRq7_9Wflong"
}
},
{
"cell_type": "code",
"source": [
"install_dates_dict = {}\n",
"for row_1 in df[df['event'] == 'app_install'][['date', 'device_id']].itertuples(index=False):\n",
" install_dates_dict[row_1[1]] = row_1[0]\n",
"\n",
"df['install_date'] = df['device_id'].apply(lambda x: install_dates_dict.get(x))\n",
"df['install_same_day'] = df['install_date'] == df['date']"
],
"metadata": {
"id": "ipV5MkXCUYYA"
},
"execution_count": 123,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Создадим сводную таблицу *open_app_df,* в которой подсчитаем количество пользователей, открывших приложение в день установки (столбец *install_same_day*) и в другие дни (столбец *others*). Дополнительно рассчитаем долю каждой группы в дневном объёме событий. Для визуализации полученных результатов используем график. По оси абсцисс расположим даты, по оси ординат - количество пользователей, открывших приложение, в разрезе выделенных групп."
],
"metadata": {
"id": "lYh3Q6ZUlWUu"
}
},
{
"cell_type": "code",
"source": [
"open_app_df = pd.pivot_table(df[df['event'] == 'app_start'], values=['device_id'], index=['date'], columns=['install_same_day'], aggfunc=len, fill_value=0).reset_index()\n",
"open_app_df = open_app_df.droplevel(1, axis=1)\n",
"open_app_df.columns = ['date', 'others', 'install_same_day']\n",
"open_app_df['others_ratio'] = round(open_app_df['others'] * 100 / (open_app_df['install_same_day'] + open_app_df['others']), 1)\n",
"open_app_df['install_same_day_ratio'] = 100 - open_app_df['others_ratio']\n",
"display(open_app_df.head())\n",
"print()\n",
"print('Ответ на первый вопрос Задания 1.1.2: {} человек установили приложение 31 марта.'.format(df[df['install_date'] == '2020-03-31']['device_id'].nunique()))\n",
"print()\n",
"print('Ответ на второй вопрос Задания 1.1.2: {:.0f}% составила доля открытий приложения 14 февраля пользователями, у которых оно уже было установлено.'.format(open_app_df[open_app_df['date'] == '2020-02-14']['others_ratio'].values[0]))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 276
},
"id": "VBrm-42BWa6v",
"outputId": "70df9016-1ad5-4ef4-a545-d4a9b9d704bd"
},
"execution_count": 124,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" date others install_same_day others_ratio install_same_day_ratio\n",
"0 2020-01-01 866 3579 19.5 80.5\n",
"1 2020-01-02 1957 3144 38.4 61.6\n",
"2 2020-01-03 2742 2402 53.3 46.7\n",
"3 2020-01-04 3093 1831 62.8 37.2\n",
"4 2020-01-05 3936 1671 70.2 29.8"
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},
{
"cell_type": "markdown",
"source": [
"***График показывает, что ежедневно на протяжении всего анализируемого периода количество пользователей, открывающих приложение в день его установки, было на порядок меньше тех, кто воспользовался установленным ранее приложением. Обратную ситуацию показывают только 1, 2 и 10 января.*** В эти дни доля пользователей, воспользовавшихся приложением в день установки превышала долю тех, кто использовал ранее установленное приложение. Возможно, большинство пользователей, установивших приложение ранее, успели воспользоваться им по назначению ещё до праздника, поэтому 1 и 2 января доля трафика от инсталлов была больше. Похожая ситуация с распределением источников трафика 10 января связана с резким ростом в этот день количества установок приложения людьми, заинтересовавшимися нашим сервисом."
],
"metadata": {
"id": "xcNUivV1Ngd5"
}
},
{
"cell_type": "markdown",
"source": [
"Посчитаем, какие каналы привлечения оказались результативнее по медианному первому чеку. Для этого создадим таблицу *first_purchase_df,* в которой оставим только первые покупки по всем покупавшим *device_id,* для чего отсортируем данные исходной таблицы по дате покупки по возрастанию и удалим строки с вторыми и последующими совпадающими *device_id.* Далее сгруппируем полученную таблицу по каналам привлечения и посчитаем количество первых покупок (понадобится далее для рассчёта конверсии) и медианный первый чек за рассматриваемый период. Отсортируем полученную таблицу по убыванию суммы чека."
],
"metadata": {
"id": "9fkjgJWNtWuH"
}
},
{
"cell_type": "code",
"source": [
"first_purchase_df = df[df['event'] == 'purchase'].sort_values('date').drop_duplicates('device_id')\n",
"first_purchase_df = first_purchase_df[['utm_source', 'device_id', 'purchase_sum']].groupby('utm_source').agg({'device_id':'count', 'purchase_sum':'median'}).reset_index()\n",
"first_purchase_df.rename({'device_id': 'purchase_count', 'purchase_sum': 'median_first_check'}, axis=1, inplace=True)\n",
"first_purchase_df.sort_values('median_first_check', ignore_index=True, ascending = False, inplace=True)\n",
"display(first_purchase_df)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 269
},
"id": "5dnwCf4FvhJn",
"outputId": "7c9d3d30-169d-46ae-9760-828b38b54ab3"
},
"execution_count": 126,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" utm_source purchase_count median_first_check\n",
"0 not_defined 14786 398.5\n",
"1 referal 5803 395.5\n",
"2 instagram_ads 9820 393.5\n",
"3 vk_ads 11460 393.0\n",
"4 yandex-direct 10936 392.5\n",
"5 google_ads 10167 390.5\n",
"6 facebook_ads 7903 389.0"
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"cell_type": "markdown",
"source": [
"***Рассчёты показали, что из платных каналов привлечения самый высокий медианный первый чек имеют пользователи, пришедшие в наш сервис по реферальной программе, а самый низкий - пользователи, пришедшие из Фейсбук.***"
],
"metadata": {
"id": "B0NOi_hu98M5"
}
},
{
"cell_type": "markdown",
"source": [
"Определим конверсию в первую покупку по каналам привлечения. Для этого объединим полученные ранее таблицы по первым открытиям приложения и первым покупкам (*first_start_df* и *first_purchase_df* соответственно) по *utm_source,* добавим столбец с конверсией открытий в покупки (в %), отсортируем полученную таблицу по убыванию значения конверсии и оставим только нужные нам столбцы."
],
"metadata": {
"id": "MZ5CgK-oJL35"
}
},
{
"cell_type": "code",
"source": [
"start_to_purchase_df = pd.merge(first_start_df, first_purchase_df, how='left', on='utm_source')\n",
"start_to_purchase_df['CR'] = round(start_to_purchase_df['purchase_count'] * 100 / start_to_purchase_df['app_start_count'], 1)\n",
"start_to_purchase_df.sort_values('CR', ignore_index=True, ascending=False, inplace=True)\n",
"start_to_purchase_df = start_to_purchase_df[['utm_source','app_start_count','purchase_count','CR']]\n",
"display(start_to_purchase_df)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 269
},
"id": "mFzvFL0gwYgA",
"outputId": "a1255cbe-8288-4dff-852b-308910c09a8d"
},
"execution_count": 127,
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"source": [
"***Как мы видим, самую высокую конверсию в первую покупку показали пользователи, пришедшие по реферальной программе, а самую низкую - пользователи, пришедшие из Яндекса.***"
],
"metadata": {
"id": "EubXdwUAA6G5"
}
},
{
"cell_type": "markdown",
"source": [
"Теперь рассчитаем окупаемость рекламных вложений (ROMI) и оценим каналы привлечения в метриках CPO (Cost per order — стоимость заказа) и CAC (Customer Acquisition Cost — стоимость привлечения покупателя). Для этого создадим сводную таблицу *romi_df,* в которой рассчитаем выручку и количество продаж. При этом применим дополнительно условие, чтобы в таблицу не попал канал not_defined. Объединим *romi_df* с таблицей *first_purchase_df,* в которой посчитано количество новых уникальных покупателей в разрезе каналов привлечения. Создадим словарь *costs_dict* и внесём в него полученные от отдела маркетинга данные по затратам в рассматриваемом периоде на рекламу. Заполним столбец *costs* с затратами из созданного ранее словаря и рассчитаем ROMI, CPO, CAC и средний чек, а полученную таблицу отсортируем по убыванию окупаемости."
],
"metadata": {
"id": "kFDwy7wFJVkw"
}
},
{
"cell_type": "code",
"source": [
"romi_df = pd.pivot_table(df[(df['event'] == 'purchase') & (df['utm_source'] != 'not_defined')], values=['purchase_sum'], index=['utm_source'], aggfunc=['sum', 'count']).reset_index()\n",
"romi_df = romi_df.droplevel(1, axis=1)\n",
"romi_df = romi_df.merge(first_purchase_df[first_purchase_df['utm_source'] != 'not_defined'][['utm_source', 'purchase_count']], how='left', on='utm_source')\n",
"romi_df.columns = ['utm_source', 'revenue', 'purch_count', 'customers_count']\n",
"costs_dict = {'referal': first_purchase_df[first_purchase_df['utm_source'] == 'referal'].values[0][1] * 200, 'vk_ads': 9553531, 'instagram_ads': 8561626, 'facebook_ads': 8590498, 'yandex-direct': 10491707, 'google_ads': 10534878}\n",
"romi_df['costs'] = romi_df['utm_source'].apply(lambda x: costs_dict[x])\n",
"romi_df['ROMI'] = round((romi_df['revenue'] - romi_df['costs']) * 100 / romi_df['costs'], 1)\n",
"romi_df['CPO'] = round(romi_df['costs'] / romi_df['purch_count'], 1)\n",
"romi_df['CAC'] = round(romi_df['costs'] / romi_df['customers_count'], 1)\n",
"romi_df['avg_check'] = round(romi_df['revenue'] / romi_df['purch_count'], 1)\n",
"romi_df.sort_values('ROMI', inplace=True, ignore_index=True, ascending=False)\n",
"display(romi_df)\n",
"print()\n",
"print('Ответ на вопросы Задания 1.1.8: Из платных каналов привлечения самый высокий ROMI имеет \"{}\", а самый низкий ROMI имеет \"{}\".'.format(romi_df['utm_source'][0], romi_df['utm_source'][5]))"
],
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"base_uri": "https://localhost:8080/",
"height": 272
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"id": "7n9-VIrIY9zA",
"outputId": "a83a7c56-da13-4097-e566-8e5627de0c7f"
},
"execution_count": 128,
"outputs": [
{
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" utm_source revenue purch_count customers_count costs ROMI \\\n",
"0 referal 8837044.5 12839 5803 1160600 661.4 \n",
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"2 instagram_ads 14546969.0 20176 9820 8561626 69.9 \n",
"3 facebook_ads 12249901.0 17219 7903 8590498 42.6 \n",
"4 yandex-direct 13915368.0 19359 10936 10491707 32.6 \n",
"5 google_ads 12868276.0 18479 10167 10534878 22.1 \n",
"\n",
" CPO CAC avg_check \n",
"0 90.4 200.0 688.3 \n",
"1 416.1 833.6 713.8 \n",
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"\n",
"Ответ на вопросы Задания 1.1.8: Из платных каналов привлечения самый высокий ROMI имеет \"referal\", а самый низкий ROMI имеет \"google_ads\".\n"
]
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},
{
"cell_type": "markdown",
"source": [
"***Выводы.***\n",
"\n",
"Коэффициент возврата инвестиций 661% говорит о том, что наша реферальная программа прибыльна, она приносит 6,61 рублей на каждый потраченный рубль. Остальные же рекламные кампании убыточны (ROMI < 100%), практически мы возвращаем только свои затраты на рекламу (ROMI по всем каналам положительный). Наряду с этим из расчётов видно, что с реферальной программы мы получаем покупателей с наименьшими затратами на привлечение (стоимость привлечения одного покупателя составила 200 руб.) и продажи с наименьшими расходами на заказ (стоимость заказа по реферальной программе составила 90 руб.), а превышение стоимости привлечения покупателей суммы среднего чека по остальным каналам говорит об их неэффективности.\n",
"\n",
"По результатам проведённого анализа можно сделать вывод, что реферальная программа как канал привлечения наиболее интересна для масштабирования и необходимо перераспределить на неё часть бюджета с менее эффективных каналов.\n",
"\n",
"***Предложения.***\n",
"\n",
"Для продвижения реферальной программы нужно сделать так, чтобы как можно больше пользователей узнало о ней: использовать пуш-уведомления, электронные письма и SMS с описанием преимуществ нашей программы и качественным призывом к действию (можно даже поработать над созданием чувства «срочности» у пользователей). Чтобы обнаружение реферальной программы в приложении не составило пользователю труда, кнопку имеет смысл разместить в наиболее очевидном месте – меню приложения, попробовать выделить её с помощью определенного цвета или значка, использовать мощное слово/словосочетание, которое спровоцирует пользователя нажать (например «Пригласи и заработай!». Кроме этого нужно создать понятное руководство по использованию реферальной программы, интегрировать кнопки социальных сетей и персонализированные ссылки, ведь помимо четкого представления всей процедуры пользователи должны иметь возможность быстро делиться реферальными ссылками через соц. сети и реферальные коды. Можно даже пойти на некоторое увеличение вознаграждения рефералам. \n",
"\n",
"При этом две рекламные кампании (Гугл и Яндекс), являющиеся лидерами по привлечению новых пользователей, но аутсайдерами по совокупности остальных анализируемых метрик, обязательно необходимо корректировать. Их стоит попробовать перевести на модель оплаты рекламы CPS (Cost per Sale), в которой в качестве целевого действия выступает продажа. В этом случае трафик, который мы получим, с большей вероятностью будет целевым и мы увеличим конверсию. При этом платформам будет непросто привлечь в наше приложение посетителей, готовых сделать заказ, в связи с этим необходимо будет предложить за новых покупателей солидные комиссионные. Но чтобы определить, сколько мы готовы платить за них, необходимо сначала рассчитать, какую прибыль приносит средняя продажа, а для этого необходимы данные по всем затратам.\n",
"\n",
"Важно вводить перечисленные выше изменения с проведением тестирования каждой выдвинутой гипотезы, с постоянным мониторингом целевых показателей, своевременно и гибко реагируя на изменения отслеживаемых метрик."
],
"metadata": {
"id": "LmVp3k9cDVyR"
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},
{
"cell_type": "markdown",
"source": [
"**2. Анализ воронки продаж.**"
],
"metadata": {
"id": "kK2705QLbGHN"
}
},
{
"cell_type": "markdown",
"source": [
"Для начала работы по построению воронки продаж добавим в исходную таблицу столбец с датой регистрации пользователей и определим для каждого события, какие из них были совершены зарегистрированными, а какие незарегистрированными пользователями.\n",
"\n",
"Создадим словарь *register_dates_dict*, содержащий *device_id* и соответствующие даты регистрации и с помощью lambda-функции пройдёмся по значениям столбца *device_id* для заполнения из полученного словаря дат рагистрации пользователей в столбец *register_date*. Создадим новый столбец *previously_registered,* который заполним значениями True для тех событий, которые совершили зарегистрированные ранее пользователи, и False для тех событий, которые совершили ранее незарегистрированные пользователи (сюда же отнесём события, которые произошли в день регистрации)."
],
"metadata": {
"id": "Z58YDZpoM2Tb"
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},
{
"cell_type": "code",
"source": [
"register_dates_dict = {}\n",
"for row_2 in df[df['event'] == 'register'][['date', 'device_id']].itertuples(index=False):\n",
" register_dates_dict[row_2[1]] = row_2[0]\n",
" \n",
"df['register_date'] = df['device_id'].apply(lambda x: register_dates_dict.get(x))\n",
"df['previously_registered'] = df['date'] > df['register_date']\n",
"display(df.head())"
],
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"id": "bL6r4jkOs02v",
"outputId": "440aeff5-7055-4eaa-d781-1d73bc3c14a0"
},
"execution_count": 129,
"outputs": [
{
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" date event purchase_sum os_name device_id gender \\\n",
"0 2020-01-01 app_start NaN android 669460 female \n",
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"2 2020-01-01 app_start NaN android 1579237 male \n",
"3 2020-01-01 app_start NaN android 1737182 female \n",
"4 2020-01-01 app_start NaN ios 4029024 female \n",
"\n",
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"2 Saint-Petersburg referal NaT False \n",
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"source": [
"Сформируем воронку продаж по зарегистрированным пользователям. Для этого создадим сводную таблицу *reg_users_funnel_df,* в которой подсчитаем количество уникальных зарегистрированных пользователей на каждом этапе воронки продаж. Чтобы учесть только зарегистрированных пользователей применим к исходной таблице условие равенства значения True в столбце *previously_registered.* Отсортируем полученную таблицу по количеству пользователей, совершивших каждое действие, по убыванию.\n",
"\n",
"Также будет полезно выяснить процент пользователей, которые добавили товар в корзину, но не совершили покупку. В этом нам поможет метрика CAR (Shopping Cart Abandonment Rate — коэффициент брошенных корзин), рассчитаем её по формуле: 1 – (Количество покупок / Количество добавлений в корзину)."
],
"metadata": {
"id": "4-WZw3Dlg5yy"
}
},
{
"cell_type": "code",
"source": [
"reg_users_funnel_df = pd.pivot_table(df[df['previously_registered'] == True], values='device_id', index='event', aggfunc='nunique').reset_index()\n",
"reg_users_funnel_df.rename({'device_id': 'users_count'}, axis=1, inplace=True)\n",
"reg_users_funnel_df.sort_values('users_count', ignore_index=True, ascending = False, inplace=True)\n",
"reg_users_car = 1 - (reg_users_funnel_df['users_count'][4] / reg_users_funnel_df['users_count'][2])\n",
"display(reg_users_funnel_df)\n",
"print()\n",
"print('Коэффициент брошенных корзин по зарегистрированным клиентам составил {:.0%}.'.format(reg_users_car))"
],
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{
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"text": [
"\n",
"Коэффициент брошенных корзин по зарегистрированным клиентам составил 34%.\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"Теперь сформируем воронку продаж по незарегистрированным пользователям. Для этого создадим сводную таблицу *unreg_users_funnel_df,* в которой подсчитаем количество уникальных незарегистрированных пользователей на каждом этапе воронки продаж. Чтобы учесть только незарегистрированных пользователей применим к исходной таблице условие равенства значения False в столбце *previously_registered.* При этом применим дополнительно условие, чтобы в этапы воронки не попало событие установки приложения, так как данные по этому событию будут нерепрезентативны (часть пользователей, которые совершают события в рассматриваемом периоде, установили приложение ранее). Отсортируем полученную таблицу по количеству пользователей, совершивших каждое действие, по убыванию.\n",
"Дополнительно рассчитаем коэффициент брошенных корзин по незарегистрированным пользователям.\n",
"\n",
"Для визуализации полученных результатов используем воронку из модуля plotly.graph_objects библиотеки plotly, а чтобы разместить несколько графиков на одном окне используем функцию make_subplots, в которой укажем необходимое количество столбцов.\n",
"\n",
"Столбцами в объединённом окне будут воронки продаж отдельно по зарегистрированныи и незарегистрированным пользователям. В каждом графике приведём значения этапов воронки продаж в количественном и процентном выражении, конверсию отразим относительно предыдущего этапа воронки."
],
"metadata": {
"id": "onDy9PQnjp2r"
}
},
{
"cell_type": "code",
"source": [
"unreg_users_funnel_df = pd.pivot_table(df[(df['previously_registered'] == False) & (df['event'] != 'app_install')], values='device_id', index='event', aggfunc='nunique').reset_index()\n",
"unreg_users_funnel_df.rename({'device_id': 'users_count'}, axis=1, inplace=True)\n",
"unreg_users_funnel_df.sort_values('users_count', ignore_index=True, ascending = False, inplace=True)\n",
"unreg_users_car = 1 - (unreg_users_funnel_df['users_count'][5] / unreg_users_funnel_df['users_count'][2])\n",
"display(unreg_users_funnel_df)\n",
"print()\n",
"print('Коэффициент брошенных корзин по незарегистрированным клиентам составил {:.0%}.'.format(unreg_users_car))"
],
"metadata": {
"id": "tAlXTNZZuPCP",
"colab": {
"base_uri": "https://localhost:8080/",
"height": 272
},
"outputId": "19c5b194-bcff-4632-874d-6885790df7d9"
},
"execution_count": 131,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" event users_count\n",
"0 app_start 190884\n",
"1 search 184488\n",
"2 choose_item 155691\n",
"3 tap_basket 125414\n",
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"5 purchase 67753"
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"\n",
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},
{
"cell_type": "markdown",
"source": [
"**Выводы.**\n",
"\n",
"Проведённый анализ показал, что из зарегистрированных пользователей наибольшее количество \"отваливается\" на этапе оформления покупки (его совершают лишь 72% пользователей, перешедших в корзину), а коэффициент брошенных корзин составляет 34%.\n",
"\n",
"Можно предположить, что некоторые пользователи заходят в корзину в надежде обнаружить скидку или промокод на покупку, сравнить цены с аналогами или же изучить отличия продукта от аналогичных товаров в нише, некоторые заходят, чтобы составить список желаемых покупок на будущее. Заставить этот тип покупателей приобрести товар будет крайне затруднительно. Важнее сфокусировать внимание на пользователях, готовых и способных совершить покупку, а также понимать, почему они этого не сделали. Возможно, их смутило возникновение какой-либо проблемы во время оформления заказа (слишком долгий процесс чекаута, невозможность рассчитать итоговую стоимость заказа заранее, недостаточное количество способов оплаты, ошибка применения промокода) или высокая стоимость доставки.\n",
"\n",
"Самым \"сложным\" этапом прохождения воронки продаж для незарегистрированных пользователей оказалась регистрация (её успешно проходят лишь 62% пользователей, перешедших в корзину), а коэффициент брошенных корзин по таким пользователям составил 56%. \n",
"\n",
"**Предложения.**\n",
"\n",
"\"Отвалившимся\" зарегистрированным пользователям через некоторое время после неудачного завершения процесса покупки необходимо направлять на электронную почту (у нас есть их контактные данные) письма с просьбой указать причину, по которой они не стали завершать покупку, ведь зная наиболее частые причины брошенных корзин мы сможем устранить их путем оптимизации приложения, доработки процесса чекаута или просчитать возможность снижения стоимости доставки. Такими действиями мы с большой вероятностью сможем повысить лояльность клиентов.\n",
"\n",
"Для уменьшения количества \"отваливающихся\" незарегистрированных пользователей нужно поработать над упрощением процесса регистрации (обязательно перепроверив его на баги) или добавить в него элементы геймификации, чтобы прогресс пользователя в заполнении данных о себе сопровождался неким повышением \"статуса\" или \"звания\", level-up, финальным уровнем которого будет завершение регистрации и получение пользователем награды в виде, к примеру, промокода (действующего определённое время после регистрации) или скидки / бесплатной доставки к первому заказу (можно продумать условие минимальной суммы заказа, чтобы ещё увеличить средний чек). Можно также рассмотреть возможность добавления функции быстрой покупки без регистрации (\"в один клик\"), так как некоторых пользователей мог просто смутить запрос на создание аккаунта в приложении.\n",
"\n",
"Вероятно, какая-то часть из всех \"отвалившихся\" пользователей может вернуться к заказу сама, но мы можем дополнительно попытаться улучшить коэффициент брошенных корзин, применив систему ремаркетинга - напомнив о товарах в корзине и, при возможности, предоставив скидку!"
],
"metadata": {
"id": "5_e9Wxw2oX-Y"
}
},
{
"cell_type": "markdown",
"source": [
"**3. Когортный анализ пользователей приложения.**"
],
"metadata": {
"id": "gXp7E-M6LT-t"
}
},
{
"cell_type": "markdown",
"source": [
"Для разделения пользователей на когорты по дате первого визита в приложение и дате первой покупки необходимо добавить в исходную таблицу столбцы с соответствующими датами.\n",
"\n",
"Создадим промежуточную таблицу *first_start_date_df*, содержащую данные о датах первых открытий приложения, сгруппированные по столбцу *device_id,* а также таблицу *first_purch_date_df*, содержащую данные о датах первых покупок, сгруппированные по столбцу *device_id.* Присоединим к исходной таблице *df* обе созданные ранее таблицы с датами по *device_id.*"
],
"metadata": {
"id": "PghdokogLoHN"
}
},
{
"cell_type": "code",
"source": [
"first_start_date_df = df[df['event'] == 'app_start'][['device_id', 'date']].groupby('device_id').agg(min).reset_index()\n",
"first_start_date_df.rename({'date': 'first_start_date'}, axis=1, inplace=True)\n",
"first_purch_date_df = df[df['event'] == 'purchase'][['device_id', 'date']].groupby('device_id').agg(min).reset_index()\n",
"first_purch_date_df.rename({'date': 'first_purchase_date'}, axis=1, inplace=True)\n",
"df = df.merge(first_start_date_df, how='left', on='device_id').merge(first_purch_date_df, how='left', on='device_id')"
],
"metadata": {
"id": "zjLTv-xBYc8N"
},
"execution_count": 133,
"outputs": []
},
{
"cell_type": "markdown",
"source": [
"Исходя из специфики бизнеса по доставке продуктов на дом сделаем предположение, что большинство пользователей в среднем делают заказ продуктов раз в неделю. В целях проведения когортного анализа будем формировать недельные когорты пользователей. \n",
"\n",
"Создадим копию таблицы *df* и назовём её *cohorts_df.* В ней мы переведём все даты событий, даты регистрации, даты первого открытия приложения и первой покупки в недели с помощью аксессора dt.to_period('W') и удалим ставшие ненужными столбцы. Добавим столбцы *fs_cohort_week* и *fp_cohort_week,* в которых посчитаем количество дней существования когорт по неделе первого посещения и по неделе первой покупки относительно каждого события, а затем конвертируем их в номера недель жизни когорт с помощью целочисленного деления на 7."
],
"metadata": {
"id": "m72Y1ASWV6We"
}
},
{
"cell_type": "code",
"source": [
"cohorts_df = df.copy()\n",
"cohorts_df['week'] = cohorts_df['date'].dt.to_period('W').apply(lambda x: x.start_time)\n",
"cohorts_df['register_cohort'] = cohorts_df['register_date'].dt.to_period('W').apply(lambda x: x.start_time)\n",
"cohorts_df['first_start_cohort'] = cohorts_df['first_start_date'].dt.to_period('W').apply(lambda x: x.start_time)\n",
"cohorts_df['first_purchase_cohort'] = cohorts_df['first_purchase_date'].dt.to_period('W').apply(lambda x: x.start_time)\n",
"cohorts_df = cohorts_df.drop(columns=['date', 'install_date', 'install_same_day', 'register_date', 'previously_registered', 'first_start_date', 'first_purchase_date'])\n",
"cohorts_df['fs_cohort_week'] = cohorts_df['week'] - cohorts_df['first_start_cohort']\n",
"cohorts_df['fs_cohort_week'] = cohorts_df['fs_cohort_week'].apply(lambda x: x.days // 7 )\n",
"cohorts_df['fp_cohort_week'] = cohorts_df['week'] - cohorts_df['first_purchase_cohort']\n",
"cohorts_df['fp_cohort_week'] = cohorts_df['fp_cohort_week'].apply(lambda x: x.days // 7 )\n",
"cohorts_df['fp_cohort_week'].fillna(0, inplace=True)\n",
"cohorts_df['fp_cohort_week'] = cohorts_df['fp_cohort_week'].astype(int)\n",
"display(cohorts_df.head())"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 206
},
"id": "gvRcAufpazC1",
"outputId": "3d37bb0f-20c0-4d3d-ce51-1d9990a49b32"
},
"execution_count": 134,
"outputs": [
{
"output_type": "display_data",
"data": {
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" event purchase_sum os_name device_id gender city \\\n",
"0 app_start NaN android 669460 female Moscow \n",
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{
"cell_type": "markdown",
"source": [
"Теперь сформируем когорты пользователей по неделе первого посещения. Для этого создадим сводную таблицу *fs_cohort_df,* в которой подсчитаем количество уникальных пользователей в каждой когорте понедельно в динамике за весь срок существования когорты. На основании полученной таблицы создадим также таблицу *fs_cohort_df2,* в которой посчитаем возвращаемость пользователей сформированных когорт. Для визуализации полученных результатов используем тепловую карту из библиотеки seaborn. Импортируем необходимые библиотеки. По оси абсцисс расположим номера недель жизни когорт, по оси ординат - когорты по неделе первого посещения."
],
"metadata": {
"id": "oWfpBtmFAsv_"
}
},
{
"cell_type": "code",
"source": [
"fs_cohort_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'app_start'], index='first_start_cohort', columns='fs_cohort_week', values='device_id', aggfunc='nunique').reset_index()\n",
"fs_cohort_df['first_start_cohort'] = fs_cohort_df['first_start_cohort'].astype(str)\n",
"fs_cohort_df.set_index('first_start_cohort', inplace=True)\n",
"fs_cohort_df2 = fs_cohort_df.apply(lambda x: round(x * 100 / fs_cohort_df[0]))\n",
"print('Ответ на вопрос Задания 1.2.1: Самой активной когортой по неделе первого посещения стала когорта {}.'.format(fs_cohort_df.sum(axis=1).sort_values(ascending=False).index[0]))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "OwI4f_e5dycm",
"outputId": "ff5f0804-a80a-46e7-e4ed-7db2840236e0"
},
"execution_count": 135,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Ответ на вопрос Задания 1.2.1: Самой активной когортой по неделе первого посещения стала когорта 2019-12-30.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"import seaborn as sns\n",
"import matplotlib.pyplot as plt\n",
"\n",
"plt.figure(figsize=(20, 10))\n",
"fig = sns.heatmap(fs_cohort_df, annot=True, fmt=',.0f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=150, vmax=30000)\n",
"fig.set_title('Активность пользователей когорт по неделе первого посещения, чел.', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Когорта по неделе первого посещения', size= 14)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 627
},
"id": "OsEBkWuhehdc",
"outputId": "a7baec1e-5718-4fa2-cb09-722ecc2c65f6"
},
"execution_count": 136,
"outputs": [
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"output_type": "display_data",
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],
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"***Самой многочисленной когортой по неделе первого посещения является когорта от 06.01.2020г. Самой активной когортой является когорта 30.12.2019г. (абсолютный лидер по возвращаемости пользователей среди когорт, возвращаемость по остальным когортам падает заметно быстрее начиная уже с первой недели жизни).*** "
],
"metadata": {
"id": "SROB0R8DnP5z"
}
},
{
"cell_type": "markdown",
"source": [
"Теперь сформируем когорты пользователей по неделе первой покупки. Для этого создадим сводную таблицу *fp_cohort_df,* в которой подсчитаем количество уникальных пользователей в каждой когорте понедельно в динамике за весь срок существования когорты. На основании полученной таблицы создадим также таблицу *fp_cohort_df2,* в которой посчитаем коэффициент повторных покупок (Repeat Purchase Rate) пользователей сформированных когорт. Визуализируем полученные результаты с помощью тепловой карты. По оси абсцисс расположим номера недель жизни когорт, по оси ординат - когорты по неделе первой покупки."
],
"metadata": {
"id": "jC22_UrVhF9T"
}
},
{
"cell_type": "code",
"source": [
"fp_cohort_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'purchase'], index='first_purchase_cohort', columns='fp_cohort_week', values='device_id', aggfunc='nunique').reset_index()\n",
"fp_cohort_df['first_purchase_cohort'] = fp_cohort_df['first_purchase_cohort'].astype(str)\n",
"fp_cohort_df.set_index('first_purchase_cohort', inplace=True)\n",
"fp_cohort_df2 = fp_cohort_df.apply(lambda x: round(x * 100 / fp_cohort_df[0]))"
],
"metadata": {
"id": "UWkmT8w0iv2V"
},
"execution_count": 138,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(20, 10))\n",
"fig = sns.heatmap(fp_cohort_df, annot=True, fmt=',.0f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=50, vmax=10000)\n",
"fig.set_title('Активность пользователей когорт по неделе первой покупки, чел.', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Когорта по неделе первой покупки', size= 14)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 627
},
"id": "_D4as6Foi6kw",
"outputId": "85bcddaa-9db1-4fa6-fc7d-4c31e02fc3e1"
},
"execution_count": 139,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"
"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"***Самой активной когортой по неделе первой покупки является когорта от 30.12.2019г. (абсолютный лидер по коэффициенту повторных покупок, у остальных когорт коэффициент падает сильнее, начиная с первой недели жизни). Самой многочисленной является когорта от 13.01.2020г.*** Динамика численности когорт по неделе первой покупки приблизительно повторяет динамику численности когорт по неделе привлечения, однако заметно снижение доли привлекаемых пользователей, в итоге переходящих к заказу товаров."
],
"metadata": {
"id": "UCRhRM6guMz0"
}
},
{
"cell_type": "markdown",
"source": [
"Посмотрим на размер медианного чека у когорт по неделе первой покупки. Для этого создадим сводную таблицу *fp_cohort_median_df,* в которой подсчитаем сумму медианного чека в каждой когорте понедельно в динамике за весь срок существования когорты. Для визуализации полученных результатов снова используем тепловую карту. По оси абсцисс расположим номера недель жизни когорт, по оси ординат - когорты по неделе первой покупки."
],
"metadata": {
"id": "ojLCSdtmkjnS"
}
},
{
"cell_type": "code",
"source": [
"fp_cohort_median_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'purchase'], index='first_purchase_cohort', columns='fp_cohort_week', values='purchase_sum', aggfunc='median').reset_index()\n",
"print('Ответ на вопрос Задания 1.2.4: Медианный чек на неделе первой покупки выше у когорты {}.'.format(fp_cohort_median_df.iloc[fp_cohort_median_df[0].argmax(), 0].strftime('%d-%m-%Y')))\n",
"fp_cohort_median_df['first_purchase_cohort'] = fp_cohort_median_df['first_purchase_cohort'].astype(str)\n",
"fp_cohort_median_df.set_index('first_purchase_cohort', inplace=True)"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/"
},
"id": "WdqZ6_X58grg",
"outputId": "d9f34aaa-3b6b-41cc-8664-e769aaf653ac"
},
"execution_count": 141,
"outputs": [
{
"output_type": "stream",
"name": "stdout",
"text": [
"Ответ на вопрос Задания 1.2.4: Медианный чек на неделе первой покупки выше у когорты 09-03-2020.\n"
]
}
]
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(20, 10))\n",
"fig = sns.heatmap(fp_cohort_median_df, annot=True, fmt='.1f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=330, vmax=450)\n",
"fig.set_title('Медианный чек когорт по неделе первой покупки, руб.', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Когорта по неделе первой покупки', size= 14)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 629
},
"id": "Ap7LpBp09XB2",
"outputId": "b07d8bc5-eb59-4e55-aba1-9794fefc75e4"
},
"execution_count": 142,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"
\n",
" "
]
},
"metadata": {}
}
]
},
{
"cell_type": "markdown",
"source": [
"Чтобы понять, в какой когорте сосредоточены платящие клиенты, приносящие максимальный доход, рассчитаем метрику ARPPU (средний доход на одного платящего пользователя). Для начала создадим сводную таблицу *fp_cohort_revenue_df,* в которой подсчитаем понедельно суммы продаж в каждой когорте. Разделим полученные данные по продажам на еженедельное количество уникальных платящих клиентов по когортам из таблицы *fp_cohort_df* и результат запишем в переменную *fp_cohort_arppu_df*. Визуализируем полученные результаты с помощью тепловой карты. По оси абсцисс расположим номера недель жизни когорт, по оси ординат - когорты по неделе первой покупки."
],
"metadata": {
"id": "hABdz-ueOXOQ"
}
},
{
"cell_type": "code",
"source": [
"fp_cohort_revenue_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'purchase'], index='first_purchase_cohort', columns='fp_cohort_week', values='purchase_sum', aggfunc='sum').reset_index()\n",
"fp_cohort_revenue_df['first_purchase_cohort'] = fp_cohort_revenue_df['first_purchase_cohort'].astype(str)\n",
"fp_cohort_revenue_df.set_index('first_purchase_cohort', inplace=True)\n",
"fp_cohort_arppu_df = fp_cohort_revenue_df / fp_cohort_df"
],
"metadata": {
"id": "3ag8J7RaMcuu"
},
"execution_count": 147,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(20, 10))\n",
"fig = sns.heatmap(fp_cohort_arppu_df, annot=True, fmt=',.0f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=500, vmax=1100)\n",
"fig.set_title('Средний доход на одного платящего клиента (ARPPU), руб.', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Когорта по неделе первой покупки', size= 14)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 629
},
"id": "SvHVJQXoOJql",
"outputId": "5da76638-fb54-4e42-9682-922b154ebd34"
},
"execution_count": 148,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"
"
],
"image/png": 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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"***Когорта 30.12.2019г. практически на протяжении всего срока жизни имеет наибольший ARPPU среди всех когорт по неделе первой покупки.***"
],
"metadata": {
"id": "n_oPUjixhxH4"
}
},
{
"cell_type": "markdown",
"source": [
"Рассчитаем метрику Purchase Frequency (частота покупок). Для этого создадим сводную таблицу *fp_cohort_purchases_df,* в которой подсчитаем понедельно количество продаж в каждой когорте. Разделим полученные данные на еженедельное количество уникальных платящих клиентов по когортам из таблицы *fp_cohort_df* и результат запишем в переменную *purchases_frequency_df*. Визуализируем полученные результаты с помощью тепловой карты. По оси абсцисс расположим номера недель жизни когорт, по оси ординат - когорты по неделе первой покупки."
],
"metadata": {
"id": "vkneiaS1Yl26"
}
},
{
"cell_type": "code",
"source": [
"fp_cohort_purchases_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'purchase'], index='first_purchase_cohort', columns='fp_cohort_week', values='event', aggfunc=len).reset_index()\n",
"fp_cohort_purchases_df['first_purchase_cohort'] = fp_cohort_purchases_df['first_purchase_cohort'].astype(str)\n",
"fp_cohort_purchases_df.set_index('first_purchase_cohort', inplace=True)\n",
"purchase_frequency_df = fp_cohort_purchases_df / fp_cohort_df"
],
"metadata": {
"id": "ZwtNzrzAPLQ0"
},
"execution_count": 149,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(20, 10))\n",
"fig = sns.heatmap(purchase_frequency_df, annot=True, fmt='.1f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=1, vmax=1.5)\n",
"fig.set_title('Частота совершения покупок (Purchase Frequency), раз', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Когорта по неделе первой покупки', size= 14)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 627
},
"id": "o0iOOPiQWT9Y",
"outputId": "226affd3-409d-4a9b-d368-073b0aed5233"
},
"execution_count": 150,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
"
"
],
"image/png": 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},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"***Частота совершения покупок клиентами из когорты 30.12.2019г. выше, чем у остальных когорт. В среднем активные клиенты этой когорты совершают 1,4 покупки в неделю.***"
],
"metadata": {
"id": "Zfv5ke61iZbb"
}
},
{
"cell_type": "markdown",
"source": [
"Посмотрим на то, какая когорта принесла нам больше всего денег за период своего существования. Для этого создадим сводную таблицу *fp_cohort_LTV_df,* в которой подсчитаем итоговую сумму продаж в каждой когорте по неделе первой покупки."
],
"metadata": {
"id": "dgxw2wETi-Ir"
}
},
{
"cell_type": "code",
"source": [
"fp_cohort_LTV_df = pd.pivot_table(cohorts_df[cohorts_df['event'] == 'purchase'], index='first_purchase_cohort', values='purchase_sum', aggfunc='sum').reset_index()\n",
"fp_cohort_LTV_df.rename({'purchase_sum': 'LTV'}, axis=1, inplace=True)\n",
"display(fp_cohort_LTV_df)\n",
"print()\n",
"print('Ответ на вопрос Задания 1.2.3: Больше всего денег принесла когорта {}.'.format(fp_cohort_LTV_df.iloc[fp_cohort_LTV_df['LTV'].argmax(), 0].strftime('%d-%m-%Y')))"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 523
},
"id": "uTvPRLpb4LS-",
"outputId": "7ecfb516-7b15-47bd-d724-e8a1ef6bd2d2"
},
"execution_count": 151,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
" first_purchase_cohort LTV\n",
"0 2019-12-30 12320177.5\n",
"1 2020-01-06 19787838.0\n",
"2 2020-01-13 18852452.0\n",
"3 2020-01-20 9018049.5\n",
"4 2020-01-27 7432634.0\n",
"5 2020-02-03 6305237.0\n",
"6 2020-02-10 6766314.0\n",
"7 2020-02-17 5398837.5\n",
"8 2020-02-24 3067633.5\n",
"9 2020-03-02 3629773.0\n",
"10 2020-03-09 2099374.5\n",
"11 2020-03-16 2099173.0\n",
"12 2020-03-23 2895260.0\n",
"13 2020-03-30 584207.0"
],
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2020-02-17
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"metadata": {}
},
{
"output_type": "stream",
"name": "stdout",
"text": [
"\n",
"Ответ на вопрос Задания 1.2.3: Больше всего денег принесла когорта 06-01-2020.\n"
]
}
]
},
{
"cell_type": "markdown",
"source": [
"***Когорта от 06.01.2020г. заработала больше всего денег за период своего существования. Максимальная численность когорты от 13.01.2020г. позволила ей стать второй по результативности, несмотря на самые низкие из тройки лидеров показатели ARPPU и Repeat purchase rate. Когорта 30.12.2019г., имея самые высокие показатели ARPPU и Repeat purchase rate, заняла лишь 3-е место в списке самых результативных когорт по сумме заработанных денег, что произошло по причине её малочисленности (4464 чел. в сравнении с 10903 чел. и 13621 чел. в когортах-лидерах).***"
],
"metadata": {
"id": "P5rIQaKPL0yS"
}
},
{
"cell_type": "markdown",
"source": [
"Проведём небольшое исследование состава когорты, оказавшейся наилучшей по показателям возвращаемости, ARPPU и частоты покупок, чтобы попытаться составить \"портрет\" наших самых лояльных и прибыльных клиентов.\n",
"\n",
"Для этого создадим копию таблицы *cohort_df,* оставив только события \"покупка\", совершённые пользователями когорты 30.12.2019г., и запишем её в переменную *first_fp_cohort_df.* Создадим из неё сводную таблицу, в которой в качестве строк используем такие данные о клиенте, как город, пол и ОС устройства, в качестве столбцов номера недель жизни когорты, а в значениях посчитаем количество уникальных пользователей. Визуализируем полученные результаты с помощью тепловой карты. По оси абсцисс расположим номера недель жизни когорты, по оси ординат - подгруппы в разрезе города, пола пользователей и ОС устройства."
],
"metadata": {
"id": "Jduce4x4T2R3"
}
},
{
"cell_type": "code",
"source": [
"first_fp_cohort_df = cohorts_df[(cohorts_df['event'] == 'purchase') & (cohorts_df['first_purchase_cohort'] == '2019-12-30')].copy()\n",
"first_fp_cohort_df = pd.pivot_table(first_fp_cohort_df, values='device_id', index=['city', 'gender', 'os_name'], columns='fp_cohort_week', aggfunc='nunique')\n",
"first_fp_cohort_df = first_fp_cohort_df.apply(lambda x: round(x * 100 / x.sum(), 1))"
],
"metadata": {
"id": "Xj-9qsfYZyhH"
},
"execution_count": 152,
"outputs": []
},
{
"cell_type": "code",
"source": [
"plt.figure(figsize=(20, 6))\n",
"fig = sns.heatmap(first_fp_cohort_df, annot=True, fmt='.1f', annot_kws={'size': 11}, cmap= 'Blues', linewidths= 1, vmin=5, vmax=20)\n",
"fig.set_title('Состав покупателей когорты 30-12-2019 по неделе первой покупки, %', size= 16)\n",
"fig.set_xlabel('Номер недели', size= 14)\n",
"fig.set_ylabel('Город, пол и ОС устройства', size= 13)\n",
"plt.show()"
],
"metadata": {
"colab": {
"base_uri": "https://localhost:8080/",
"height": 410
},
"id": "-nhxriEbahLP",
"outputId": "879d1fbf-3859-4a8e-cc95-7c3f2650e8bd"
},
"execution_count": 153,
"outputs": [
{
"output_type": "display_data",
"data": {
"text/plain": [
""
],
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\n"
},
"metadata": {
"needs_background": "light"
}
}
]
},
{
"cell_type": "markdown",
"source": [
"В момент формирования когорты она состояла на 57% из жителей Москвы и на 43% из жителей Санкт-Петербурга. В период жизни когорты можно заметить постепенное снижение доли пользователей из Москвы - к концу рассматриваемого периода она снизилась до 49%. Снижение доли произошло за счёт сильного оттока пользователей мужского пола (с 29% при формировании когорты их доля упала до 18% в конце периода) вне зависимости от ОС устройства, при этом доля пользователей женского пола выросла (с 28% при формировании когорты до 32% в конце периода). Рост доли пользователей из Санкт-Петербурга сформирован увеличением долей пользователей женского пола (с 24% при формировании когорты их доля выросла до 29% в конце периода) и мужского пола (с 20% увеличилась до 22% в конце периода). \n",
"\n",
"По гендерному составу в момент формирования когорта состояла из двух практически равных частей: пользователи женского пола составили 52%, а мужского - 48%. Однако к концу рассматриваемого периода структура изменилась: пользователи женского пола составили 60%, а мужского - 40%.\n",
"\n",
"**Выводы.**\n",
"\n",
"Сложившаяся ситуация с резким снижением возвращаемости пользователей в сервис уже со второй недели использования и дальнейшим падением к нему интереса наглядно иллюстрирует нам то, что можно привлекать качественный трафик и наращивать аудиторию, но без достаточных усилий по удержанию клиентов мы будем бесконечно тратить деньги. Согласно статьи The Value of Keeping the Right Customers (Ценность удержания нужных клиентов), опубликованной на сайте Harvard Business Review, привлечь нового клиента стоит в 5–25 раз дороже, чем удержать существующего **(1).** В статье \"Prescription for cutting costs\" (Рецепт для сокращения расходов) аналитик компании Bain & Company, входящей в «большую тройку» лидеров управленческого консалтинга, указывает на то, что по результатам исследований увеличение показателя retention на 5% влечет за собой рост дохода более чем на 25% **(2).** Именно удерживая пользователей и превращая их в лояльных клиентов, мы можем рассчитывать на рост. \n",
"\n",
"По результатам проведённого когортного анализа пользователей наиболее перспективной для проведения дальнейшего исследования является когорта покупателей от 30.12.2019г. Она имеет самые высокие показатели Repeat purchase rate, ARPPU и Purchase Frequency. Проведя исследование этой когорты можно использовать полученные выводы в работе с пользователями более многочисленных когорт, сделать работу над ошибками и применить их при разработке новой маркетинговой стратегии.\n",
"\n",
"Из проведённого нами исследования состава указанной когорты можно сделать вывод, что наиболее лояльной аудиторией оказались пользователи женского пола, а меньше всего наш сервис устроил пользователей мужского пола (необходим более детальный анализ обеих подгрупп). \n",
"Также прослеживается некоторое влияние ОС устройств на динамику состава когорты: пользователи с устройствами на ОС ios при прочих равных условиях либо показывают большее снижение доли, либо меньший её рост. Необходимо более детальное исследование, возможно в приложении под ОС ios есть какие-то баги/сложности.\n",
"\n",
"**Предложения.**\n",
"\n",
"Для улучшения удержания пользователей в нашем сервисе необходимо предпринять несколько шагов:\n",
"1. Продумать эффективную программу лояльности, которая из простых клиентов сделает постоянных, ведь как показывают результаты глобального исследования The Loyalty Report 2020, проведённого Visa и Bond Brand Loyalty, участники персонализированной программы лояльности остаются с брендом в 5.4 раза дольше и тратят в 6.4 раза больше **(3).** Своими рекомендациями такие клиенты бесплатно приведут к нам новых клиентов и благотворно повлияют на имидж компании. \n",
"\n",
"2. Периодически устраивать конкурсы, розыгрыши и акции, проводить опросы, увеличивая, таким образом, целевую аудиторию. Опросы также помогут выявить проблемы с интерфейсом или работоспособностью приложения, со скоростью доставки заказов или с недостаточным ассортиментом товаров. \n",
"\n",
"3. Использовать товарные рекомендации с учетом истории покупок, персональные подборки товаров, скидки на товары, которые ранее просматривал пользователь или добавил в список желаний.\n",
"\n",
"4. Давать клиентам возможность оставлять обратную связь о компании, анализировать её, отвечать на комментарии, разбирать конфликтные ситуации и решать их. Это вызовет доверие со стороны текущих и даже потенциальных клиентов."
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"\n",
"\n",
"---\n",
"\n",
"***Источники:***\n",
"\n",
"(1) https://hbr.org/2014/10/the-value-of-keeping-the-right-customers\n",
"\n",
"(2) https://media.bain.com/Images/BB_Prescription_cutting_costs.pdf\n",
"\n",
"(3) https://retail-loyalty.org/news/trendy-programm-loyalnosti-v-2020-godu-issledovanie-visa-i-bond-brand-loyalty-/"
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